In speech communication, signals from a receiver can merge into signals received by the transmitter via circuitry reflection and acoustic reflection, and are fed to a remote end, resulting in echo there. Echo may interfere with both sides in communication, impact quality of communication and even cause howling in severe cases, which not only makes communication completely impossible, but also might damage communication equipments.
Echo are typically suppressed in speech communication in order to guarantee communication quality and equipment safety. The principle of echo cancellation is as follows: echo signals are generated from receiver signal that are electro-acoustically transformed into practical sound signals to be played back and then reflected by the environment. Both the electro-acoustic conversion process in the receiver and the circumstance reflection may be considered as filtering processes, therefore echo signals may be considered as being generated from receiver signal passing a specific filter.
With traditional methods, a suitable filter is designed to cancel echo so as to eliminate echo signals from receiver signal and prevent echo from interfering with the communication. Reflection environment in actual environment change in real time, which the filter needs to track. Therefore, adaptive filters are generally used as echo path cancellation filters for echo cancellation. The filter may automatically track variation of echo reflecting environment in real time by comparing a receiver signal and a transmitter signal to obtain an accurate echo path for echo cancellation.
Challenges in designing adaptive filters are as follows: 1. In view of the time-varying actual reflection circumstance, the filter must be able to follow changes in time in case that reflection circumstance changes, which means a rapid reaction speed. 2. In case of complex reflection environment and long echo path, it is required that the filter can reflect details of the reflection environment and faithfully simulate the echo path for better echo cancellation and echo residual as little as possible. 3. The filter should not be interfered with by noises and speech at a near end. Generally speaking, the filter design is desired to be rapid, accurate and robust.
Conventional adaptive filtering is typically implemented in time domain or frequency domain. Frequency domain adaptive filtering includes Fourier Transform adaptive filtering, sub-band adaptive filtering and other adaptive filtering in form of time-frequency transformation such as those disclosed in Patent Applications Nos. 200910025855, 200780001928, 200580003444 and 200610144055. Time domain filters react fast to echo and may track echo environment rapidly. However they have more echo residues. Frequency domain adaptive filtering allows for more delicate filter update and low echo residues, but with slow reaction speed. At the moment the communication environment varies, echo would increase significantly, interfering with communication.
It is difficult for a single filter to address both reaction speed and echo residue concerns. Therefore, multiple filters are employed for collective echo cancellation in echo cancellation systems with high performance. Parallel convergence of multiple filters was adopted in the Patent Application No. 200780020102 in which the one with best echo cancellation performance is selected at any given instant as the primary filter for echo cancellation. Some of the multiple filters have a tracking speed first update strategy and some have an echo path estimation accuracy first update strategy. However, with this method utilizing parallel structure, it's necessary to determine accurately convergence of individual filters with different performance and select a currently optimal filter for switching to the filter at different moments. Therefore, they have disadvantages of hard-to-realize system structure and poor stability due to the complex logic.